Theoretical study of the synthesis of superheavy nuclei with Z= 119 and 120 in heavy-ion reactions with trans-uranium targets

By using a newly developed di-nuclear system model with a dynamical potential energy surface---the DNS-DyPES model, hot fusion reactions for synthesizing superheavy nuclei (SHN) with the charge number Z = 112-120 are studied. The calculated evaporation residue cross sections are in good agreement with available data. In the reaction 50Ti+249Bk -> (299-x)119 + xn, the maximal evaporation residue (ER) cross section is found to be about 0.11 pb for the 4n-emission channel. For projectile-target combinations producing SHN with Z=120, the ER cross section increases with the mass asymmetry in the incident channel increasing. The maximal ER cross sections for 58Fe+244Pu and 54Cr + 248Cm are relatively small (less than 0.01 pb) and those for 50Ti+249Cf and 50Ti+251Cf are about 0.05 and 0.25 pb, respectively.Comment: 6 pages, 5 figures; Phys. Rev. C, in pres

Evidence for Two Gaps and Breakdown of the Uemura Plot in Ba0.6_{0.6}K0.4_{0.4}Fe2_2As2_2 Single Crystals

We report a detailed investigation on the lower critical field $H_{c1}$ of the superconducting Ba$_{0.6}$K$_{0.4}$Fe$_2$As$_2$ (FeAs-122) single crystals. A pronounced kink is observed on the $H_{c1}(T)$ curve, which is attributed to the existence of two superconducting gaps. By fitting the data $H_{c1}(T)$ to the two-gap BCS model in full temperature region, a small gap of $\Delta_a(0)=2.0\pm 0.3$ meV and a large gap of $\Delta_b(0)=8.9\pm 0.4$ meV are obtained. The in-plane penetration depth $\lambda_{ab}(0)$ is estimated to be 105 nm corresponding to a rather large superfluid density, which points to the breakdown of the Uemura plot in FeAs-122 superconductors.Comment: 5 pages, 4 figure

The entanglement in one-dimensional random XY spin chain with Dzyaloshinskii-Moriya interaction

The impurities of exchange couplings, external magnetic fields and Dzyaloshinskii--Moriya (DM) interaction considered as Gaussian distribution, the entanglement in one-dimensional random $XY$ spin systems is investigated by the method of solving the different spin-spin correlation functions and the average magnetization per spin. The entanglement dynamics at central locations of ferromagnetic and antiferromagnetic chains have been studied by varying the three impurities and the strength of DM interaction. (i) For ferromagnetic spin chain, the weak DM interaction can improve the amount of entanglement to a large value, and the impurities have the opposite effect on the entanglement below and above critical DM interaction. (ii) For antiferromagnetic spin chain, DM interaction can enhance the entanglement to a steady value. Our results imply that DM interaction strength, the impurity and exchange couplings (or magnetic field) play competing roles in enhancing quantum entanglement.Comment: 12 pages, 3 figure

China CO2 emission accounts 1997–2015

China is the world’s top energy consumer and CO2 emitter, accounting for 30% of global emissions. Compiling an accurate accounting of China’s CO2 emissions is the first step in implementing reduction policies. However, no annual, officially published emissions data exist for China. The current emissions estimated by academic institutes and scholars exhibit great discrepancies. The gap between the different emissions estimates is approximately equal to the total emissions of the Russian Federation (the 4th highest emitter globally) in 2011. In this study, we constructed the time-series of CO2 emission inventories for China and its 30 provinces. We followed the Intergovernmental Panel on Climate Change (IPCC) emissions accounting method with a territorial administrative scope. The inventories include energy-related emissions (17 fossil fuels in 47 sectors) and process-related emissions (cement production). The first version of our dataset presents emission inventories from 1997 to 2015. We will update the dataset annually. The uniformly formatted emission inventories provide data support for further emission-related research as well as emissions reduction policy-making in China

Study on integrated energy microgrid energy purchase strategy with demand-side response in market environment

Integrated energy microgrids (IEM) have emerged as an effective way to improve energy efficiency and promote distributed energy utilization. IEM systems acquire electricity and gas from external markets and supply electricity/heat/cold to users. In this paper, we study the optimal energy purchase strategy for IEM, considering the impact of demand response incentives. Firstly, considering the uncertainties, we construct an IEM medium- and long-term market multi-energy purchase model based on conditional value-at-risk, optimizing the portfolio of electricity and gas purchases, as well as their proportion in total energy amount. Subsequently, based on medium- and long-term daily energy supply curves and day-ahead load forecast results, a spot market energy purchase model is established to optimize the spot purchase of electricity and gas, maintaining the supply-demand balance while minimizing operating costs. Furthermore, we design demand response incentives and develop a master-slave game model between IEM and users to guide the formulation of the energy purchase strategy by incorporating corrected load data as feedback. The energy purchase strategies are resolved by the GUROBI solver, while the optimization of demand response incentives is carried out through the PSO algorithm, all based on the MATLAB platform. The adaptability of the proposed model and strategy is verified

Influence of Carbon Concentration on the Superconductivity in MgCxNi3

The influence of carbon concentration on the superconductivity (SC) in MgC$_{x}$Ni$_3$ has been investigated by measuring the low temperature specific heat combined with first principles electronic structure calculation. It is found that the specific heat coefficient $\gamma_n=C_{en}/T$ of the superconducting sample ($x\approx1$) in normal state is twice that of the non-superconducting one ($x\approx 0.85$). The comparison of measured $\gamma_n$ and the calculated electronic density of states (DOS) shows that the effective mass renormalization changes remarkably as the carbon concentration changes. The large mass renormalization for the superconducting sample and the low $T_{c}$(7K) indicate that more than one kind of boson mediated electron-electron interactions exist in MgC$_{x}$Ni$_3$.Comment: 4 pages, 4 figure

Pressure Effect on the superconducting properties of LaO_{1-x}F_{x}FeAs(x=0.11) superconductor

Diamagnetic susceptibility measurements under high hydrostatic pressure (up to 1.03 GPa) were carried out on the newly discovered Fe-based superconductor LaO_{1-x}F_{x}FeAs(x=0.11). The transition temperature T_c, defined as the point at the maximum slope of superconducting transition, was enhanced almost linearly by hydrostatic pressure, yielding a dT_c/dP of about 1.2 K/GPa. Differential diamagnetic susceptibility curves indicate that the underlying superconducting state is complicated. It is suggested that pressure plays an important role on pushing low T_c superconducting phase toward the main (optimal) superconducting phase.Comment: 7 pages, 4 figure

Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits

Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10−8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10−31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction